GenAI vs. Agentic AI: Cutting Through the Hype

Here’s a funny thought to start your day: Remember that time when every new app proudly claimed to be powered by “Machine Learning,” but in reality, it was just a cleverly tuned Excel spreadsheet with a marketing halo? Well, history has a way of repeating itself. The latest trend? Calling things as “Agentic AI,” even when it’s really just GenAI and LLM in a fancy suit.

?

Artificial Intelligence has evolved by leaps and bounds, introducing groundbreaking innovations that sound almost magical. But with great buzzwords comes great confusion. To be fair, I was too for a long time. So I did what any curious engineer would do; I started reading, researching and playing around with the tech. Here’s what I learned on my journey to understand the difference between Generative AI (GenAI) and Agentic AI.

?

What’s the Difference?

?

Generative AI focusses on creating. It generates responses, drafts summaries even writes a beautifully crafted essay ready. It excels in generating content—whether that’s text, images, or even code—based on a vast ocean of data. Tools like GPT, DALL·E, and others fall squarely in this camp. They’re excellent at “producing” but they don’t inherently understand what they’ve created.

?

Agentic AI, on the other hand, focusses on action. It is your no-nonsense colleague who focusses on doing the tedious, manual work many have asked themselves “I can’t believe I get paid to do this”. Agentic AI not only understands the nuances of the problem but also takes decisive steps to solve it. Agentic AI is designed to reason, make decisions, and execute actions in real-world environments.

Basically, think of it as the difference between a content creator and a problem solver who can act autonomously.

?

The Current Hype: Old Tricks in New Marketing

?

If your LinkedIn feeds are anything like mine, you’ve likely seen an explosion in vendors touting their “Agentic AI” capabilities. But if you take a closer look, and for many of them it’s just GenAI wearing sunglasses indoors. Sure, it’s impressive when a chatbot can write a convincing email, but that’s not the same as an AI agent autonomously reasoning about your business needs, negotiating deals, or scheduling multi-faceted logistics.

?

We’ve been here before. In the 2010s, every analytics tool was labeled “AI,” even if it only involved basic statistical modeling. Before that, “Machine Learning” was slapped on anything remotely data-driven. Now, it seems “Agentic AI” is being used as the new label for flashy but fundamentally unchanged GenAI capabilities.

?

Why It Matters

?

Here’s the thing: the distinction between GenAI and Agentic AI isn’t just technical—it’s about real-world value. Agentic AI can tackle use cases that involve reasoning, planning, and execution. For example:

·????? Managing end-to-end supply chain optimization autonomously.

·????? Diagnosing and repairing software or hardware issues without human intervention.

·????? Acting as a virtual assistant that can handle complex workflows, not just answer queries.

GenAI, for all its brilliance, isn’t designed to make autonomous decisions or take complex actions without direct input and guidance. And that’s okay! Each has its strengths.

?

Cutting Through the Noise

Before jumping on the “Agentic AI” bandwagon, consider your use cases. Do they involve reasoning and action, or are you mostly focused on generating content or responses? Understanding this difference can save you from buying into unnecessary hype and, worse, investing in solutions that don’t meet your needs.

?

Call to Action

As customers and industry leaders, we must cut through the noise and seek clarity. When vendors pitch their AI solutions, ask the hard questions:

·????? Can it reason and act autonomously, or does it just generate outputs?

·????? What are the specific use cases I need to solve, and how complex are they?

·????? Is this a true technological breakthrough or just a marketing relabeling?

Don’t get me wrong. The future of AI is undoubtedly the more exciting generational technology breakthrough we’ve been part of, but the key to unlocking its potential lies in knowing what you’re looking for and cutting through the noise. Let’s leave the hype to the marketers and focus on building solutions that drive real value.

So, next time you see a post about Agentic AI, pause and ask yourself: Is it an action hero or just a creative storyteller in disguise?

?

#AI #GenAI #AgenticAI #Technology #Innovation

?